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Risk and Protection Profile for Substance
Abuse Prevention in Washington Communities:
Great Northern School District
Spokane County
4.57-32091:2009
Research & Data Analysis Division
Vera Barga, B.S.
Irina V. Sharkova, Ph.D.
Liz Kohlenberg, Ph.D.
in conjunction with the
Division of Behavioral Health and Recovery
David Dickinson, Director
These tables provide a comprehensive update of data published in previous Profiles . They are among the
timeliest data available to planners for understanding the risks of substance abuse among youth in
their communities. Community, family, peer, and school-related factors are presented within the Hawkins
and Catalano risk and protective factor framework that is used by many substance abuse prevention
planners across the country.
These data are reported by the lowest geography available for each indicator, beginning with school
districts, followed by the locale, county, and state levels of geography.
Locales are single school districts or groups of school districts. If school districts are grouped into a single
locale, the following rules were used:
i. The total population within the grouping had to be at least 20,000 people.
ii. The school districts grouped were part of a single Educational Service District.
iii. The school districts grouped were similar in character (for example, they had similar proportions of
students receiving school lunches).
For more information about the data, framework, definitions, and other topics, see the 1997 Profile on Risk
and Protection for Substance Abuse Prevention Planning in Washington State, (Report4.15-40).
That report and subsequent years’ Profiles are available on the RDA website at:
www1.dshs.wa.gov/rda/research/risk.shtm.
Great Northern School District
Table of contents:
Cover page
Introduction
Interpreting Indicator Profiles:
Interpreting Annual Trend Charts:
Indicator Comparison Profiles: (A comparison of standarized five-year rates at county
and 'county like us' levels by domain, factor, and indicator)
1. Indicator Profile 1
2. Indicator Profile 2
3. Indicator Profile 3
4. Indicator Profile 4
Community:
5. Availability of Drugs
6. Extreme Economic & Social Deprivation
7. Transitions & Mobility
8. Alcohol or Drug-related Problems
9. Adult Violent Crime
10. Low Neighborhood Attachment and Community Disorganization
Family:
11. Family Problems
Schools:
12. Senior Class Loss
13. Low School Test Scores
Individual/Peer:
Each school district of interest is associated with information from the county in which it is located and the locale to
which the district has been assigned.
School District: Great Northern School District
County: Spokane County
Locale 7 7
District Total Locale
County Population Population
District # School District County (Census 2000) (Census 2000)
32033 Cheney S.D. Spokane County 25,205 44,116
32082 Freeman S.D. Spokane County 3,488
32091 Great Northern S.D. Spokane County 588
32121 Liberty S.D. Spokane County 3,561
32136 Medical Lake S.D. Spokane County 11,274
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009.
Standardized Five-Year Indicator Profile
Domain/Factor Indicators My County My Locale My District
Community Domain
The Indicator
Profile allows you -0.25
Availability of Drugs Alcohol Retail Licenses 0.56
to compare the 0.32
5-year standardized
rates in County, -0.26
Tobacco Retail and Vending Locale, and School 1.06
Availability of Drugs
Machine Licenses District for each 0.51
indicator by domain
Extreme Family and summary -0.54
Food Stamp Recipients 1.20
Economic measures (factors).
(All Ages) 1.12
Deprivation
Extreme Family Temporary Assistance to -0.82
Economic Needy Families (TANF), 1.29
1.31
Deprivation Child Recipients
Extreme Family Hyperlinked titles will take you -0.22
Unemployed Persons
Economic to the Domain page or the
(Age 16+)
Deprivation Some
indicator trend to see the data
-0.75 Indicators
Transitions and Net Migration,comprising the 5 year rate.
3 Year Moving are only
Mobility Average (inactive in pdf form) available
at county
-0.12 levels
Transitions and
Existing Home Sales
Mobility
-0.71
Transitions and
New Residence Construction
Mobility
-0.14
Alcohol- or Drug-Related -0.04
AOD Problems -0.03
Deaths
Clients of State-Funded -0.22 Each Summary
0.34
AOD Problems Alcohol or Drug Services 0.20 Measure (factor)
(Age 18+) has 1 to 8
-1.24 indicators.
Arrests, Alcohol-Related (Age -1.07
18+) -1.16
-0.63
Arrests, Drug Law Violation 0.76
AOD Problems 0.57
(Age 18+)
1.47
Arrests, Violent Crime 3.67
Adult Violent Crime 3.76
(Age 18+)
-4 0 4
lower state rate higher
If the 5 year rate was suppressed for data problems, there will be no bar or label. Rates equal to the state mean have a 0.0 label.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009.
Understanding the CORE Community Level Trend Charts and Tables
The presentation of risk factor data in the CORE reports is organized by domain (Community, Family, School, and
Individual/Peer) and by risk factor within domains. Each risk factor may include one or more indicators. In the
Community Reports, each indicator is presented for a school district, the locale in which the district is located, the
county, and the state.
The CORE Community Reports may help to answer questions such as:
What are the levels for indicators of risk and youth problem behavior in our community?
How do my community's indicators compare with neighboring communities, the county, and the state?
Do all of the indicators for a given risk factor in my community follow a common trend?
Do the indicators suggest particular areas of risk in need of intervention?
Please note these IMPORTANT ISSUES:
The workbook tabs are labeled with the name of the risk factor. Each risk factor may in turn include several indicators.
Be sure to scroll down the page to review all of the available indicators for a given risk factor. The workbook is
designed to print with one indicator on each page.
Data may be suppressed (not reported).
Each chart provides indicator data for all available geographic levels, including the school district, the locale, the county
and the state. In some instances data cannot be reliably reported for very small areas -- for example, school districts --
so the spaces where that data would be presented is left blank. When data or rates are suppressed, a suppression
code is listed. The suppression codes are explained in the Technical Notes. Note that suppressed data can appear as
a "0" value in the trend lines or as a missing bar. These data should not be interpreted as "0," rather, the data should
be treated as unknown for that year.
Understanding the chart scales:
Users should be careful to interpret the chart scales correctly. The chart scales are automatically adjusted to enhance
differences between the indicators at each geographic level. Users should consider whether the differences they
observe between geographic areas or across years are significant. The unit of measurement is displayed at the left of
each chart scale. Often the unit of measurement is a rate expressed as the number of events or a count of individuals
per 100 population (or, "percent"), or sometimes per 1,000 or 100,000 population.
Review the example:
On the following page (below, scroll down) is an example indicator for Alcohol Retail Licenses in "My School District,"
located in "Cascadia County." The number of alcohol retail licenses is expressed as a rate per 1,000 population. In
1994, the number of alcohol retail licenses per 1,000 population in in "My School District" was more than three times
that of the state average and over twice the county average. The rate in "My School District" was also higher than the
average for Locale 999, suggesting that the rate was higher in "My School District" than in neighboring communities
(users would need to to check the reports for surrounding communities who are included in Locale 999 to verify this.)
Note that in the example, data were not reported for this school district in 1996. This resulted in an apparent value of
"0" for the "My School District" bar and the "Locale 999" line. These values should not be interpreted as "0." Rather,
they should be treated as missing. An explanation of the suppression code in the table below the trend chart appears
in the Technical Notes section of this report.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009.
Pay close attention to these scales. The differences between
the state, county, locale, and district rates may appear more or
less important depending on the scale used.
Alcohol Retail Licenses
7
When rates are suppressed a
suppression code is listed.
6 These codes are explained in
Technical Notes. Be aware
Rate Per
5 that these values when
1,000 graphed can seem to indicate
4 a zero value rate in trend lines
or a missing bar.
3
Units for the chart
scale. Rates are 2
expressed as the
number per 100 1
(percent), 1,000
or 100,000 0
population. My School District State Cascadia County Locale 999
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
State 1.55 1.67 1.89 1.90 2.03 2.05 2.07 1.91 1.89 1.78 1.66 1.59
Cascadia County 2.12 2.06 2.03 2.01 2.01 2.01 2.00 1.98 1.96 1.91 1.91 1.91
Locale 999 3.27 3.12 NR 3.08 2.98 3.00 2.96 2.88 2.77 3.17 3.17 3.17
My School District 5.08 5.23 NR 5.22 5.29 5.35 4.86 4.99 4.32 5.93 5.85 5.89
Licenses 32 34 35 36 37 38 35 35 31 43 43 43
All Persons 6,295 6,497 6,703 6,899 7,000 7,103 7,198 7,012 7,177 7,250 7,350 7,298
Note: The rates are the annual number of alcohol retail licenses active during the year, per 1,000 persons (all ages). Retail
licenses include restaurants, grocery stores, and wine shops but do not include state liquor stores and agencies. Retail alcohol
Explanation of not licensed
facilities on military bases and reservations arerate calculationby the State and therefore are not included in these data. Policies on
the = (numerator / determining factor
licensing distributors, taxingRate proceeds, anddenominator) x who can sell alcohol varies substantially from state to state.
Consequently, there is no Example in 1994: 32 ÷ 6,295 X for national data. Data from 1999 to present is now geocoded from the
consistent comparable source 1,000 = 5.08
In rather than apportioned from zip code. This "My School more accurate, but different data total per county.
facility address, 1994, there were 5.08 licenses per 1,000 people in results in a District."
State Source: Washington State Liquor Control Board, Annual Operations Report
Population Estimates: Washington State Department of Health, Vista Partnership, Krupski Consulting; Washington State
Population Estimates for Public Health. October 2004.
The latest 5-years of data
Each indicator graph is followed by data source and rate definitions as
well as any special information for the data.
are used to calculate the 5-
year average used in the
Updated standardized indicators
1/27/2005 When the newest
data was added.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009.
Standardized Five-Year Indicator Profile
Domain/Factor Indicators 0 Locale 7 Great Northern School District
Community Domain
-0.18
Availability of Drugs Alcohol Retail Licenses -0.31
-0.28
Tobacco Retail and Vending -0.43
Availability of Drugs
Machine Licenses
Extreme Family 0.73
Food Stamp Recipients -0.36
Economic
(All Ages)
Deprivation
Extreme Family Temporary Assistance to 0.28
Economic Needy Families (TANF), -0.83
Deprivation Child Recipients
Extreme Family 0.13
Unemployed Persons
Economic
(Age 16+)
Deprivation
-0.14
Transitions and Net Migration, 3 Year Moving
Mobility Average
0.10
Transitions and
Existing Home Sales
Mobility
0.19
Transitions and
New Residence Construction
Mobility
0.06
Alcohol- or Drug-Related 0.75
AOD Problems
Deaths
Clients of State-Funded 0.45
0.60
AOD Problems Alcohol or Drug Services
(Age 18+)
-1.49
Arrests, Alcohol-Related (Age -0.31
18+)
-0.29
Arrests, Drug Law Violation -0.32
AOD Problems
(Age 18+)
0.49
Arrests, Violent Crime 0.06
Adult Violent Crime
(Age 18+)
-4 0 4
lower state rate higher
If the 5 year rate was suppressed for data problems, there will be no bar or label. Rates equal to the state mean have a 0.0 label.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 1
Standardized Five-Year Indicator Profile
Domain/Factor
0 Locale 7 Great Northern School District
Indicators
Community Domain
Low Neighborhood -0.09
Prisoners in State
Attachment and Correctional Systems
Community (Age 18+)
Disorganization
-0.24
Population Not Registered to
Vote
Low Neighborhood
Attachment and Registered and Not Voting in -0.22
Community the November Election
Disorganization
Family Domain
0.44
Family Problems Divorce
Victims of Child Abuse and 0.47
Family Problems Neglect in Accepted -0.23
Referrals
School Domain
-0.71
Freshmen Who Leave
0.01
Senior Class Loss School Before Their Senior
Year
-0.28
Low School Test Poor Academic Performance, -0.14
Scores Grade 10 WASL (Age 15)
-0.28
Low School Test Poor Academic Performance, -0.59
Scores Grade 7 WASL (Age 12)
-0.58
Low School Test Poor Academic Performance, -0.30
Scores Grade 4 WASL (Age 9)
Individual/Peer Domain 0.04
0.73
Early Criminal Justice Arrests, Alcohol- or Drug-
Involvement Related (Age 10-14)
-0.25
-0.11
Early Criminal Justice Arrests, Vandalism
Involvement (Age 10-14)
-4 0
lower state rate higher
If the 5 year rate was suppressed for data problems, there will be no bar or label. Rates equal to the state mean have a 0.0 label.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 2
Standardized Five-Year Indicator Profile
Domain/Factor Indicators
0 Locale 7 Great Northern School District
Problem Outcomes
Child and Family Child Injury and Accident 0.81
0.99
Health Hospitalizations
Child and Family Infant Mortality 0.18
1.51
Health (Under 1 Year)
Child and Family Child Mortality 0.05
Health (Ages 1-17) 0.18
Child and Family Births -0.16
Health (Mothers Age 10-17) -0.56
Sexually Transmitted
Child and Family -0.24
Disease Cases
Health
(Birth-19)
Child and Family Suicide and Suicide Attempts 1.84
Health (Age 10-17) 1.32
Child and Family 0.17
Low Birth Weight Babies
Health -0.16
Child and Family Women Injury and Accident 1.53
Health Hospitalizations 0.98
School Weapons Incidents
School Issues -1.59
All Grades -1.35
-1.41
lower state rate higher
If the 5 year rate was suppressed for data problems, there will be no bar or label. Rates equal to the state mean have a 0.0 label.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 3
Standardized Five-Year Indicator Profile
Domain/Factor Indicators
0 Locale 7 Great Northern School District
Problem Outcomes
0.52
Criminal Justice Offences, Domestic Violence -0.78
-0.29
Criminal Justice Total Arrests, (Age 10-14) 0.11
-0.34
Arrests, Property Crime -0.19
Criminal Justice
(Age 10-14)
-0.29
Arrests, Property Crime -0.33
Criminal Justice
(Age 10-17)
-0.88
Arrests, Property Crime -0.55
Criminal Justice
(Age 18+)
0.59
Arrests, Violent Crime 0.24
Criminal Justice
(Age 10-17)
Alcohol-Related Traffic -0.31
Substance Use Fatalities Per All Traffic
Fatalities
-0.34
Arrests, Alcohol Violation 0.39
Substance Use
(Age 10-17)
0.19
Arrests, Drug Law Violation 0.62
Substance Use
(Age 10-17)
Clients of State-Funded 0.74
Substance Use Alcohol or Drug Services -0.24
(Age 10-17)
lower state rate higher
If the 5 year rate was suppressed for data problems, there will be no bar or label. Rates equal to the state mean have a 0.0 label.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 4
Community Domain: Availability of Drugs
Alcohol Retail Licenses Go To Standardized Five-Year Rate indicator Comparison Profile
12
Rate Per 9
1,000
6
3
0
Great Northern School District State Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 1.92 1.90 1.88 1.90 1.92 1.96 1.97 1.95 1.96 1.97
Spokane County 1.65 1.64 1.63 1.64 1.65 1.70 1.75 1.73 1.74 1.77
Locale 7 1.50 1.50 1.43 1.51 1.57 1.67 1.63 1.70 1.73 1.69
Great Northern School District UN UN UN UN UN UN UN UN UN UN
Licenses 2 2 2 2 2 2 1 1 2 2
All Persons 573 587 602 603 575 581 624 715 780 849
Note: The rates are the annual number of alcohol retail licenses active during the year, per 1,000 persons (all ages). Retail
licenses include restaurants, grocery stores, and wine shops but do not include state liquor stores and agencies. Retail alcohol
facilities on military bases and reservations are not licensed by the State and therefore are not included in these data. Policies
on licensing distributors, taxing the proceeds, and determining who can sell alcohol vary substantially from state to state.
Consequently, there is no consistent comparable source for national data. Data from 1999 to present is now geocoded from the
facility address, rather than apportioned from zip code. This results in a more accurate, but different data total per county.
State Source: Washington State Liquor Control Board, Annual Operations Report
Population Estimates: Washington State Department of Health, Vista Partnership
Updated
4/23/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 5
Community Domain: Availability of Drugs
Tobacco Retail and Vending Machine Licenses Go To Standardized Five-Year Rate indicator Comparison Profile
25
Rate Per
20
1,000
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 1.53 1.48 1.44 1.40 1.36 1.32 1.28 1.14 1.27 1.11
Spokane County 1.32 1.31 1.29 1.23 1.16 1.12 1.10 0.95 1.03 0.93
Locale 7 1.03 1.16 1.12 1.05 1.11 1.11 0.98 1.00 1.09 0.93
Great Northern School District UN UN UN UN UN UN UN UN UN UN
Licenses 0 0 0 0 0 0 0 1 1 0
All Persons 573 587 602 603 575 581 624 715 780 849
Note: The rates are the annual number of tobacco retailer and vending machine licenses active during the year, per 1,000
persons (all ages). Tobacco retailers on military bases and reservations are not licensed by the State and therefore are not
included in these data. Tobacco sales licenses include tobacco retailer licenses (stores that sell tobacco products) and tobacco
vending machines. November counts are selected as representative of the average yearly number of retailers. No source of
comparable national data was obtained.
State Source: Department of Health (from the Department of Licensing), Tobacco Prevention Program, Tobacco Statistics
Population Estimates: Washington State Department of Health
Updated
4/20/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 6
Community Domain: Extreme Family Economic Deprivation
Food Stamp Recipients (All Ages) Go To Standardized Five-Year Rate indicator Comparison Profile
180
Rate Per 160
1,000 140
120
100
80
60
40
20
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 97.78 87.74 87.43 94.67 103.46 112.47 119.99 121.92 121.43 126.43
Spokane County 125.09 119.77 119.34 127.88 140.87 151.91 161.41 164.06 164.22 164.13
Locale 7 82.28 79.65 76.49 79.58 86.52 90.40 93.99 100.65 100.15 98.46
Great Northern School District UN UN UN UN UN UN UN UN UN UN
Recipients 110 83 102 118 127 104 98 97 118 135
All Persons 573 587 602 603 575 581 624 715 780 849
Note: The rate is the number of persons (all ages) receiving food stamps in the fiscal year, per 1,000 persons (all ages).
National rates use counts of all yearly recipients. Suppression code definitions for yearly rates are explained in Technical Notes
State Source: Department of Social and Health Services, Research and Data Analysis, Automated Client Eligibility System and
Warrant Roll. Population Estimates: Washington State Department of Health
National Source: US Census Bureau, Statistical Abstract of the US; Federal Food Stamp Programs by State
Updated
5/10/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 7
Community Domain: Extreme Family Economic Deprivation
Temporary Assistance to Needy Families (TANF), Child Recipients
Go To Standardized Five-Year Rate indicator Comparison Profile
160
140
Rate Per 120
1,000 100
80
60
40
20
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 122.29 114.45 108.35 105.84 102.68 104.34 102.47 97.95 90.06 87.81
Spokane County 150.39 148.12 138.71 128.33 124.78 115.69 111.25 107.10 103.15 102.03
Locale 7 95.53 96.90 85.61 68.34 59.85 55.96 50.71 50.72 45.70 51.38
Great Northern School District UN UN UN UN UN UN UN UN UN UN
TANF Children 31 26 33 27 28 15 16 10 16 18
Children, birth-17 140 140 142 140 131 131 139 159 172 185
Note: The rate is the number of children (age birth-17) participating in Aid to Families (AFDC/TANF) programs in the fiscal
year, per 1,000 children (age birth-17). Nationally, prior to 1997 AFDC Flash Report was used which counts children 0-17.
However National TANF child recipients are defined as children 0-19 with almost no children of age 19, therefore national
denominators after 1996 are for children 0-18. Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Department of Social and Health Services, Research and Data Analysis, Automated Client Eligibility System
and Warrant Roll. Population Estimates: Washington State Department of Health
National Source: U.S. Department of Health & Human Services, Administration for Children and Families, Office of Planning
Research and Evaluation: Characteristics and Financial Circumstances of TANF Recipients Table I-29
Updated
5/8/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 8
Community Domain: Extreme Family Economic Deprivation
Unemployed Persons (Age 16+) Go To Standardized Five-Year Rate indicator Comparison Profile
9
8
Rate Per
7
100 6
5
4
3
2
1
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 4.87 4.78 4.85 4.96 6.19 7.34 7.41 6.26 5.53 4.99 4.54 5.34
Spokane County 4.23 4.16 4.87 5.16 6.59 7.63 7.51 6.54 5.69 5.05 4.73 5.61
Locale 7
Great Northern School District
Unemployed, 16+
Labor Force,16+
Note: The rate is unemployed persons (age 16 and over) per 100 persons in the civilian labor force. Unemployed persons are
individuals who are currently available for work have actively looked for work, and do not have a job. The civilian labor force
includes persons who are working or looking for work. The monthly numbers are a snapshot in time done approximately the 12th
of each month. A yearly estimate is then produced by averaging the monthly numbers. Historical data has been updated. 2002
data should be considered preliminary. Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Employment Security Department, Labor Market and Economic Analysis, County Unemployment File
National Source: U.S. Department of Labor Bureau of Labor Statistics Labor Force Statistics from the Current Population
Survey
Updated
4/22/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 9
Community Domain: Transitions and Mobility
Net Migration, 3 Year Moving Average Go To Standardized Five-Year Rate indicator Comparison Profile
Rate Per 14
1,000 12
10
8
6
4
2
0
Great Northern School District Spokane County
Locale 7 State
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 11.22 9.94 8.79 6.81 6.43 5.71 5.39 4.82 5.82 8.80 10.51 10.62
Spokane County 6.63 5.37 3.09 1.87 2.42 2.58 3.96 3.30 4.09 7.26 9.65 11.75
Locale 7
Great Northern School District
Resident Change
All Persons
Note: Net migration is the annual number of new residents that moved into an area minus the number of residents that moved
out of an area adding births and subtracting deaths. A 3-year moving average smooths net migration. Annual net migration
estimates are summed for 3-year ranges then averaged to calculate the numerator. The last year of the 3 years used in the
average is used for the population denominator and the year label for the average net migration value. Data is calculated from
fiscal year data, for fiscal year 1998-1999 the year designation is 1999 as an average of data from fiscal years 1996-1997 to
1998-1999. Since increases and decreases in population both cause disruption to the community, the absolute value of the
change is charted.
State Source: Office of Financial Management, Net Migration Data
Updated
11/10/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 10
Community Domain: Transitions and Mobility
Existing Home Sales Go To Standardized Five-Year Rate indicator Comparison Profile
30
Rate Per
25
1,000
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 17.86 19.67 20.61 17.50 18.21 19.29 22.36 23.97 25.51 22.68 18.61 12.99
Spokane County 14.55 16.59 16.44 17.18 18.66 20.09 20.81 22.55 26.24 24.38 20.70 14.57
Locale 7
Great Northern School District
Sales
All Persons
Note: The rates are the annual number of previously-owned homes sold, per 1,000 persons (all ages). Previously-owned homes
sold is rounded to the tens. Existing homes sold are estimated based on data from multiple listing services, firms that monitor
deeds, and local Realtors associations. Adjustments were made by the data provider to remove refinanced, rather than sold homes
from the counts of sales.
State Source: Washington Center for Real Estate Research, Washington State University, Washington State's Housing Market: A
Supply/Demand Assessment. Population Estimates: Washington State Department of Health
National Source: US Census Bureau, Statistical Abstract of the US; Existing One-family houses sold
Updated
9/9/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 11
Community Domain: Transitions and Mobility
New Residence Construction Go To Standardized Five-Year Rate indicator Comparison Profile
12
Rate Per
10
8
1,000 6
4
2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 7.25 7.95 7.34 6.65 6.42 6.69 7.07 8.18 8.59 7.89 7.33 4.39
Spokane County 4.59 6.18 5.37 5.01 5.26 5.14 6.13 9.07 10.08 8.48 6.15 5.24
Locale 7
Great Northern School District
New Residences
All Persons
Note: The rates are the annual number of new building permits issued for single and multi-family dwellings, per 1,000 persons
(all ages). Each unit in a multi-family dwelling (for example, each apartment in a building) has a separate building permit.
State Source: Washington Center for Real Estate Research, Washington State University, Washington State's Housing Market:
A Supply/Demand Assessment. Population Estimates: Washington State Department of Health
National Source: US Census Bureau, Statistical Abstract of the US; New Privately Owned Housing Units Started
Updated
9/9/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 12
Community Domain: Alcohol or Drug-related Problems
Alcohol- or Drug-Related Deaths Go To Standardized Five-Year Rate indicator Comparison Profile
25
Percent
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 9.04 8.92 8.65 8.80 8.87 9.62 10.03 10.91 11.01 11.62 11.71 11.68
Spokane County 8.65 8.38 8.20 8.43 8.82 9.45 9.55 11.32 11.07 10.92 11.86 12.17
Locale 7 9.30 10.93 8.67 8.37 9.09 11.20 11.32 13.06 10.93 13.57 13.09 12.96
Great Northern School District SN SN SN SN SN SN SN SN SN SN SN SN
AOD-related 0 0 0 1 0 0 1 1 1 1 1 1
Deaths 4 4 3 4 3 4 4 4 3 5 4 5
Note: The rates are the annual number of deaths, with alcohol- or drug-related causes, per 100 deaths. Evaluation is based on
all contributory causes of death for direct and indirect associations with alcohol and drug abuse. For a complete explanation of
the codes and methods used please see Technical Notes: Counting Alcohol- or Drug-related Deaths. Suppression code
definitions for yearly rates are explained in Technical Notes. Rates are not reported when fewer than 100 deaths occurred in an
area.
State Source: Department of Health, Center for Health Statistics, Death Certificate Data File
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 13
Community Domain: Alcohol or Drug-related Problems
Clients of State-Funded Alcohol or Drug Services (Age 18+)
Go To Standardized Five-Year Rate indicator Comparison Profile
Rate Per
35
1,000
30
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 10.52 10.96 11.20 11.64 11.47 11.82 11.98 12.73 13.32 13.47 13.83 14.19
Spokane County 12.66 13.18 13.65 14.98 14.71 14.48 15.42 15.20 14.94 16.70 17.28 17.12
Locale 7 27.41 29.93 30.46 23.98 22.92 16.09 18.73 18.53 18.42 18.46 18.19 17.98
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Admits, 18+ 15 16 15 7 9 8 11 9 7 11 11 11
Persons, 18+ 398 419 433 446 460 464 444 450 484 556 608 663
Note: The rates are the annual number of adults (age 18 and over) receiving state-funded alcohol or drug services, per 1,000
adults. Counts of adults are unduplicated so that those receiving services more than once during the year are only counted once
for that year. State-funded services include treatment, assessment, and detox. Persons in Department of Corrections treatment
programs are not included.
State Source: Department of Social and Health Services, Division of Behavioral Health and Recovery, Treatment and
Assessment Report Generation Tool (TARGET). Population Estimates: Washington State Department of Health
National Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode
Data Set (TEDS)
Updated
10/30/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 14
Community Domain: Alcohol or Drug-related Problems
Arrests (Age 18+), Alcohol-Related Go To Standardized Five-Year Rate indicator Comparison Profile
14
12
10
8
6
Rate Per
4
1,000 2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 12.50 11.14 10.95 10.20 9.93 11.27 11.80 11.75 10.64 10.75 10.44 9.65
Spokane County 5.96 5.26 6.04 4.88 4.66 2.58 3.67 3.32 3.98 3.89 2.89 2.50
Locale 7 UN UN UN UN UN UN UN 11.65 9.82 9.27 7.51 6.59
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 18+ 1 1 1 1 1 0 1 0 1 1 1 1
Adjst'd Pop 18+ 398 419 433 446 460 460 440 450 484 556 608 663
Note: The rates are the alcohol violations (age 18+), per 1,000 adults (age 18+). Alcohol violations include all crimes involving
driving under the influence, liquor law violations, and drunkenness. DUI arrests by the Washington State Patrol (29% of all
Adult Alcohol-related Arrests) are included in the state trend analysis. However, they are not included in the county rankings
since WSP arrests are not assigned to counties. Data may differ from our last report because of refinements to our population
adjustment process. Denominators are adjusted by subtracting the population of police agencies that did not report arrests to
UCR. In spite of this population adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the
rate for the county will be lower than it would be if that jurisdiction was included. For percent subtracted, suppression code
definitions and the agencies not reporting, see the Technical Notes and the appendix on Non-Reporting Agencies and
Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 15
Community Domain: Alcohol or Drug-related Problems
Arrests (Age 18+), Drug Law Violation Go To Standardized Five-Year Rate indicator Comparison Profile
40
Rate Per 35
1,000 30
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 5.53 5.62 5.41 5.93 5.86 5.45 5.78 5.31 5.38 6.40 6.20 5.10
Spokane County 6.65 6.31 7.13 7.01 7.45 3.15 5.10 4.63 5.46 4.98 5.44 4.58
Locale 7 UN UN UN UN UN UN UN 3.73 5.32 5.45 6.31 4.19
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 18+ 1 1 1 2 2 1 2 1 1 2 2 1
Adjst'd Pop 18+ 398 419 433 446 460 460 440 450 484 556 608 663
Note: The rates are the annual number of arrests of adults (age 18+) for drug law violations, per 1,000 adults (age 18+). Drug
law violations include all crimes involving sale, manufacturing, and possession of drugs. Data may differ from our last report
because of refinements to our population adjustment process. Denominators are adjusted by subtracting the population of police
agencies that did not report arrests to UCR. In spite of this population adjustment, when the non-reporting police jurisdiction is
where much of the crime occurs, the rate for the county will be lower than it would be if that jurisdiction was included. For
Note: The rates suppression code definitions and the agencies fatalities, per 100 traffic fatalities. "Alcohol-related" means
percent subtracted,are the annual number of alcohol-related trafficnot reporting, see the Technical Notes and the appendix on
Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 16
Community Domain: Adult Violent Crime
Arrests (Age 18+), Violent Crime Go To Standardized Five-Year Rate indicator Comparison Profile
12
Rate Per
Note: The rates 9are the annual number of alcohol-related traffic fatalities, per 100 traffic fatalities. "Alcohol-related" means
1,000
6
3
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 1.81 1.76 1.65 1.71 1.68 1.54 1.58 1.59 1.57 1.54 1.53 1.47
Spokane County 1.86 1.77 1.55 1.53 1.71 1.06 1.22 1.37 2.16 1.92 2.13 1.75
Locale 7 UN UN UN UN UN UN UN 1.05 2.10 1.57 1.86 1.41
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 18+ 1 1 0 0 1 0 1 0 1 1 1 1
Adjst'd Pop 18+ 398 419 433 446 460 460 440 450 484 556 608 663
Note: The rates are the annual number of arrests of adults (age 18+) for violent crime per 1,000 adults (age 18+). Violent
crimes include all crimes involving criminal homicide, forcible rape, robbery, and aggravated assault. Simple assault is not
defined as a violent crime. Data may differ from our last report because of refinements to our population adjustment process.
Denominators are adjusted by subtracting the population of police agencies that did not report arrests to UCR. In spite of this
population adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the rate for the county will
be lower than it would be if that jurisdiction was included. For percent subtracted, suppression code definitions and the agencies
not reporting, see the Technical Notes and the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 17
Community Domain: Low Neighborhood Attachment and Community Disorganization
Prisoners in State Correctional Systems (Age 18+) Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per 700
100,000 600
500
400
300
200
100
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 114.91 118.61 116.78 117.73 125.89 143.14 198.09 291.89 372.42 387.96 427.28 442.06
Spokane County 108.90 104.00 113.03 87.81 90.67 108.32 184.79 238.19 294.29 339.78 365.69 599.55
Locale 7
Great Northern School District
Prisoners, 18+
All Persons
Note: The rate is the annual number of adult (age 18 and over) admissions to prison, per 100,000 persons (all ages). Admissions
include new admissions, re-admissions, community custody inmate violations, and parole violations. Counts of admissions are
duplicated so that individuals admitted to prison more than once in a year are counted each time they are admitted. The
admissions are attributed to the county where the conviction occurred. In 2003 prisoners being electronically monitored are
included in the data. This causes a jump in numbers for counties which use this incarceration option. National data after 1998
are not available in an equivalent form. Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Department of Corrections, Inmates File. Population Estimates: Washington State Department of Health
National Source: Bureau of Justice Statistics Correctional Populations in the U.S.
Updated
8/23/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 18
Community Domain: Low Neighborhood Attachment and Community Disorganization
Population Not Registered to Vote Go To Standardized Five Year Rate Indicator Comparison Profile
35
Rate Per 30
100 25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 27.12 26.38 28.12 23.85 26.11 28.97 29.84 24.49 28.58 32.36 33.20 27.54
Spokane County 30.84 27.89 31.96 25.83 30.98 28.85 32.01 22.85 24.61 29.95 31.06 25.91
Locale 7
Great Northern School District
Not Registered
Persons, 18+
Note: The rate is the annual number of persons not registered to vote in the November elections, per 100 adults (age 18 and over).
As part of the November Current Population Survey (the Voting and Registration Supplement), the Bureau of the Census collects
data on voting and registration in years with presidential or congressional elections (i.e. every other year).
State Source: Office of the Secretary of State, Elections Division, Registered Voters. Population Estimates: Washington State
Department of Health
National Source: Calculated using data from U.S. Census Bureau, Statistical Abstract of the United States; "Voting-Age
Population, Percent Reporting Registered, and Voted: 1980 to 2000"
Updated
2/25/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 19
Community Domain: Low Neighborhood Attachment and Community Disorganization
Registered and Not Voting in the November Election
Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per 70
100 60
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 43.35 37.83 42.23 24.54 55.49 43.65 59.51 17.81 45.18 35.45 49.96 15.39
Spokane County 39.18 40.92 40.66 23.98 56.54 41.35 53.55 18.84 45.92 33.20 45.23 14.22
Locale 7
Great Northern School District
Not Voting
Reg'd Voters
Note: The rate is the annual number of persons registered to vote in the November elections but not voting, per 100 adults (age
18 and over) registered to vote. As part of the November Current Population Survey (the Voting and Registration Supplement),
the Bureau of the Census collects data on voting and registration in years with presidential or congressional elections (i.e. every
other year).
State Source: Office of the Secretary of State, Elections Division, Registered Voters.Population Estimates: Washington State
Department of Health
National Source: Calculated using data from U.S. Census Bureau, Statistical Abstract of the United States; "Voting-Age
Population, Percent Reporting Registered, and Voted: 1980 to 2000"
Updated
2/26/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 20
Family Domain: Family Problems
Divorce Go To Standardized Five Year Rate Indicator Comparison Profile
12
Rate Per
9
1,000
6
3
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 6.54 6.50 6.33 6.04 5.76 5.86 5.53 5.59 5.41 5.11 5.00 4.86
Spokane County 6.82 6.88 6.65 6.60 6.84 6.66 5.92 5.86 5.97 5.41 5.44 5.05
Locale 7
Great Northern School District
Divorces
Persons, 15+
Note: The State and County rates are the annual number of divorces per 1,000 persons (age 15 and over). Divorce includes
dissolutions, annulments, and unknown decree types; it does not include legal separations. Divorce data is reported by the
woman's residence, if in Washington at the time of decree. If the woman lived outside Washington, the man's residence was
used. If both parties residence was unknown the event is not assigned to a county, but is included in the state rate. The National
rate is based on age 18 and over population. Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Department of Health, Center for Health Statistics, Dissolution and Annulment Data. Population Estimates:
Washington State Department of Health
National Source: Calculated using Department of Health and Human Services, Centers for Disease Control and Prevention,
National Center for Health Statistics, National Vital Statistics System, National Vital Statistics Reports Births, Marriages,
Divorces, and Deaths, Provisional Data
Updated
9/23/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 21
Family Domain: Family Problems
Victims of Child Abuse and Neglect in Accepted Referrals
Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per 60
1,000 50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 38.88 40.63 39.43 37.60 40.87 38.06 35.26 34.30 34.15 32.07
Spokane County 35.11 37.90 37.77 39.57 50.34 42.24 41.36 41.55 42.67 41.71
Locale 7 16.32 30.40 28.14 28.94 34.06 27.93 29.62 30.36 33.13 35.76
Great Northern School District UN UN UN UN UN UN UN UN UN UN
Accepted Victims 1 6 6 7 9 6 4 5 6 7
Persons, birth-17 140 140 142 140 131 131 139 159 172 185
Note: The rates are the annual number of children (age birth-17) identified as victims in reports to Child Protective Services
that were accepted for further action, per 1,000 children (age birth-17). Children are counted more than once if they are reported
as a victim more than once during the year. A "referral" is a report of suspected child abuse. Child counts are now taken directly
from Children's Administration, Administrative Services, Case Management Information System (CAMIS) rather than from
CAMIS through Kid's Count as done in previous reports. Numbers may differ due to corrections or changes in location
definition made in the database extraction process. Child location is derived from the residence at the time of referral.
Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Department of Social and Health Services, Children's Administration, Administrative Services, Case
Management Information System (CAMIS). Population Estimates: Washington State Department of Health
National Source: US Department of Health and Human Services Administration for Children and Families, Voluntary
Cooperative Information System(VCIS), and estimates from Adoption, Foster Care Analysis Reporting System(AFCARS)
Updated
5/20/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 22
School Domain: Senior Class Loss
Freshmen Who Leave School Before Their Senior Year
A Comparison of Senior Class as a Percent of Freshman Class Enrollment
Go To Standardized Five Year Rate Indicator Comparison Profile
Percent
35
30
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 22.67 22.80 20.92 21.46 19.55 17.61 16.48 17.57 9.76 15.21 12.05 9.34
Spokane County 23.15 28.02 23.36 21.78 19.95 20.03 18.51 12.18 3.33 2.99 3.53 1.18
Locale 7 27.60 29.51 23.92 28.18 18.62 21.30 12.24 16.28 6.23 6.69 12.27 22.86
Great Northern School District 0.00 0.00
Senior Attrition 0 0
Freshman Enrollment 0 0
Note: Where senior enrollment is smaller than freshman enrollment the rate is the annual number fewer seniors as a percent of
freshman October enrollment. When senior enrollment is greater than freshman enrollment the rate is zero. The senior and
freshman classes are compared for the same school year. The method of calculation has been adjusted to minimize differences
caused by small number issues in rural areas. Results may differ from those reported in previous years. . Net migration, found on
the Transitions and Mobility pages, should be checked for large shifts of in or out migration since that can be reflected in
comparative class size.
State Source: Office of Superintendent of Public Instruction, Information Services, October Enrollment Files.
Updated
3/26/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 23
School Domain: Low School Test Scores
Poor Academic Performance, Grade 10 Washington Assessment of Student Learning (WASL)
Go To Standardized Five Year Rate Indicator Comparison Profile
Percent
90
80
70
60
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 78.69 79.88 70.51 69.78 66.38 72.68 57.51 63.92 62.97 62.80
Spokane County 77.79 79.06 66.07 65.95 61.78 69.15 55.94 62.46 60.01 62.40
Locale 7 78.88 82.98 67.69 67.43 70.65 68.78 55.38 66.74 59.21 62.64
Great Northern School District
Low Scorers
Tested, 10th grade
Note: The rates are the annual number of tenth graders who failed one or more content areas in the Washington Assessment of
Student Learning (WASL). Tests are given in the spring of the year. For example, data for 2002 is for students in the 10th
grade during the school year 2001/2002. Archived reports used 1990 Census population distributions to allocate school district
data to counties. Census population distributions for 2000 are now being used and event counts differ slightly in some counties.
By contractual agreement data is suppressed when less than ten students were tested to avoid individual student identification.
State Source: Office of Superintendent of Public Instruction, Instructional Programs, Curriculum and Assessment, Grade 10
Failing In One Or More Content Areas.
Updated
7/29/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 24
School Domain: Low School Test Scores
Poor Academic Performance, Grade 7 Washington Assessment of Student Learning (WASL)
Go To Standardized Five Year Rate Indicator Comparison Profile
100
Percent
90
80
70
60
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 88.06 84.67 81.74 80.45 77.90 72.76 63.80 58.74 60.11 53.91 57.41
Spokane County 85.15 84.10 80.76 78.98 75.52 68.31 61.81 55.01 60.26 50.89 55.34
Locale 7 85.57 87.06 85.13 76.99 73.68 65.20 58.51 50.00 51.49 50.67 51.79
Great Northern School District
Low Scorers
Tested, 7th grade
Note: The rates are the annual number of seventh graders who failed one or more content areas in the Washington Assessment
of Student Learning (WASL). Tests are given in the spring of the year. Data for 2002 is for students in the 7th grade during the
school year 2001/2002. Archived reports used 1990 Census population distributions to allocate school district data to counties.
Census population distributions for 2000 are now being used and event counts differ slightly in some counties. By contractual
agreement data is suppressed when less than ten students were tested to avoid individual student identification.
State Source: Office of Superintendent of Public Instruction, Instructional Programs, Curriculum and Assessment, Grade 7
Failing In One Or More Content Areas.
Updated
7/29/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 25
School Domain: Low School Test Scores
Poor Academic Performance, Grade 4 Washington Assessment of Student Learning (WASL)
Go To Standardized Five Year Rate Indicator Comparison Profile
Percent
90
80
70
60
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 82.42 80.97 76.68 73.30 70.86 65.56 56.39 54.78 52.83 54.08 56.47
Spokane County 81.76 80.46 74.39 69.87 66.15 58.97 49.88 48.74 49.15 51.31 50.59
Locale 7 84.69 81.76 75.09 71.99 65.34 55.24 54.23 48.40 49.45 54.22 50.88
Great Northern School District SN SN SN SN SN SN SN SN
Low Scorers 5 4 2 1 4 1 1 2
Tested, 4th grade 5 7 6 4 7 5 7 6
Note: The rates are the annual number of fourth graders who failed one or more content areas in the Washington Assessment of
Student Learning (WASL). Tests are given in the spring of the year. Data for 2002 is for students in 4th grade during the school
year 2001/2002. Archived reports used 1990 Census population distributions to allocate school district data to counties. Census
population distributions for 2000 are now being used and event counts differ slightly in some counties. By contractual agreement
data is suppressed when less than ten students were tested to avoid individual student identification.
State Source: Office of Superintendent of Public Instruction, Instructional Programs, Curriculum and Assessment, Grade 4
Failing In One Or More Content Areas.
Updated
7/29/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 26
Individual/Peer Domain: Early Criminal Justice Involvement
Arrests (Age 10-14), Alcohol- or Drug-Related
Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per
1,000 9
8
7
6
5
4
3
2
1
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 4.13 3.51 3.73 3.64 3.48 3.05 3.07 2.95 2.62 2.64 2.70 2.42
Spokane County 2.98 3.45 3.64 3.98 3.89 1.44 2.41 2.33 3.39 2.29 1.70 3.58
Locale 7 UN UN UN UN UN UN UN 2.51 7.88 5.01 4.36 3.35
Great Northern School DistrictUN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-14 0 0 0 0 0 0 0 0 0 0 0 0
Adjst'd Pop 10-14 42 43 45 46 47 47 44 44 46 51 55 58
Note: The rates are the annual number of arrests of younger adolescents (age 10-14) for alcohol and drug law
violations, per 1,000 adolescents (age 10-14). Alcohol violations include all crimes involving driving under the
influence, liquor law violations, and drunkenness. For children, arrests for liquor law violations are usually arrests
for minor in possession. Drug law violations include all crimes involving sale, manufacturing, and possession of
drugs.
1) Data may differ from our last report because of refinements to our population adjustment process. Denominators
are adjusted by subtracting the population of police agencies that did not report arrests to Uniform Crime Report
(UCR). In spite of this population adjustment, when the non-reporting police jurisdiction is where much of the
crime occurs, the rate for the county will be lower than it would be if that jurisdiction was included. For percent
subtracted, suppression code definitions and the agencies not reporting, see the Technical Notes and the appendix
on Non-Reporting Agencies and Population.
2) The DUI portion of this measure is likely understated, because arrests made by the State Patrol (approximately
40% of DUI arrests) are not attributable to counties. State Patrol arrests are included in the state rates.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40
and 50. Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics
Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 27
Individual/Peer Domain: Early Criminal Justice Involvement
Arrests (Age 10-14), Vandalism Go To Standardized Five Year Rate Indicator Comparison Profile
5
5
4
4
Rate Per 3
1,000 3
2
2
1
1
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 3.47 2.71 2.90 2.79 2.45 2.30 2.42 2.39 2.21 2.24 2.36 2.35
Spokane County 4.18 3.84 4.48 4.40 3.79 1.22 1.86 1.46 1.75 1.42 1.92 2.17
Locale 7 UN UN UN UN UN UN UN 3.13 2.21 1.88 1.56 1.22
Great Northern School DistrictUN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-14 0 0 0 0 0 0 0 0 0 0 0 0
Adjst'd Pop 10-14 42 43 45 46 47 47 44 44 46 51 55 58
Note: The rates are the annual number of arrests of younger adolescents (age 10-14) for vandalism (including
residence, non-residence, vehicles, venerated objects, police cars, or other) per 1,000 adolescents (age 10-14).
Data may differ from our last report because of refinements to our population adjustment process. Denominators
are adjusted by subtracting the population of police agencies that did not report arrests to UCR. In spite of this
population adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the rate for
the county will be lower than it would be if that jurisdiction was included. For percent subtracted, suppression
code definitions and the agencies not reporting, see the Technical Notes and the appendix on Non-Reporting
Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40
and 50. Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics
Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 28
Problem Outcomes: Child or Family Health
Injury or Accident Hospitalizations for Children Go To Standardized Five Year Rate Indicator Comparison Profile
25
Percent
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 4.01 3.77 3.60 3.82 3.67 3.65 3.34 3.87 4.21 4.03 3.86 3.95
Spokane County 5.67 5.60 4.98 4.71 5.44 5.03 4.84 5.61 6.64 5.67 5.78 5.55
Locale 7 4.37 5.06 5.67 4.27 5.72 4.96 4.02 5.89 5.87 5.78 5.29 5.37
Great Northern School District SN SN SN SN SN SN SN SN SN SN SN SN
Injuries 0 1 1 0 0 0 1 1 1 0 1 1
Hospitalizations 12 12 13 12 15 14 12 11 12 14 15 18
Note: The rate is the annual number of child injury or accident hospitalizations as a percent of all hospitalizations for children
(age birth-17). Suppression code definitions for yearly rates are explained in Technical Notes. Due to contractual agreement
data may not be displayed for areas with less than 100 hospitalizations.
State Source: Department of Health, Office of Hospital and Patient Data Systems, Comprehensive Hospital Abstract Reporting
System (CHARS)
Updated
8/25/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 29
Problem Outcomes: Child or Family Health
Infant Mortality (Under 1 Year) Go To Standardized Five Year Rate Indicator Comparison Profile
40
Rate Per 35
1,000 30
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 5.48 5.68 5.07 5.44 5.88 5.73 5.67 5.69 5.22 4.99 5.14 5.50
Spokane County 6.12 5.33 4.49 5.15 5.86 7.68 5.87 6.97 6.01 4.86 4.43 6.51
Locale 7 8.79 7.26 3.73 3.89 3.81 5.74 5.95 11.72 13.59 3.83 5.59 8.85
Great Northern School District SN SN SN SN SN SN SN SN SN SN SN SN
deaths, infants 0 0 0 0 0 0 0 0 0 0 0 0
Infants < 1 year 6 6 6 6 6 6 6 6 6 7 7 8
Note: The rate is the annual number of deaths, of infants under one year of age, per 1,000 population of infants under one year
of age. Suppression code definitions for yearly rates are explained in Technical Notes. Rates are not reported when fewer than
100 deaths occurred in an area.
State Source: Department of Health, Center for Health Statistics, Death Certificate Data File. Population Estimates: Washington
State Department of Health
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 30
Problem Outcomes: Child or Family Health
Child Mortality (Ages 1-17) Go To Standardized Five Year Rate Indicator Comparison Profile
12
Rate Per
1,000 9
6
3
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 0.28 0.24 0.24 0.24 0.22 0.23 0.22 0.21 0.21 0.19 0.18 0.18
Spokane County 0.24 0.28 0.26 0.23 0.25 0.19 0.16 0.20 0.20 0.19 0.24 0.15
Locale 7 0.00 0.38 0.29 0.29 0.19 0.39 0.20 0.20 0.00 0.19 0.47 0.18
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Child Deaths 0 0 0 0 0 0 0 0 0 0 0 0
Children (age 1-17) 129 133 134 135 136 134 126 125 133 152 165 177
Note: The rate is the annual number of deaths, of children 1 to 17 years of age, per 1,000 population of children 1 to 17 years
of age. Suppression code definitions for yearly rates are explained in Technical Notes. Rates are not reported when fewer than
100 deaths occurred in an area.
State Source: Department of Health, Center for Health Statistics, Death Certificate Data File. Population Estimates: Washington
State Department of Health
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 31
Problem Outcomes: Child or Family Health
Births (Mothers Age 10-17) Go To Standardized Five Year Rate Indicator Comparison Profile
12
Rate Per
10
1,000
8
6
4
2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 9.54 9.06 8.52 7.94 6.91 6.46 5.95 6.07 5.91 6.14 6.57 6.33
Spokane County 8.73 7.85 7.02 7.33 6.74 5.38 5.94 6.01 4.88 5.34 4.73 6.10
Locale 7 6.08 5.27 4.05 6.48 5.11 6.29 3.61 3.19 3.16 4.26 2.67 3.75
Great Northern School District SP SP SP SP SP SP SP SP SP SP SP SP
Birthed, 10-17 0 0 0 0 0 0 0 0 0 0 0 0
Females, 10-17 35 36 37 38 39 38 36 36 38 43 46 49
Note: The rate is the annual number of live births to adolescents (age 10-17) per 1,000 females (age 10-17). Rate changes in
data result from on-going updates to birth records. Suppression code definitions for yearly rates are explained in Technical
Notes. Due to contractural agreement data may not be displayed for areas with less than 100 births.
State Source: Department of Health, Center for Health Statistics, Birth Certificate Data File. Population Estimates: Washington
State Department of Health, Vista Partnership
National Source: U.S. Department of Health and Human Services, Centers for Disease Control and Health Statistics
National Center for Health Statistics, Division of Health Services, National Vital Statistics Reports
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 32
Problem Outcomes: Child or Family Health
Sexually Transmitted Disease Cases (Birth-19) Go To Standardized Five Year Rate Indicator Comparison Profile
10
Rate Per
8
1,000
6
4
2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 2.72 3.11 3.29 3.31 3.42 3.53 4.05 3.85 3.99 3.75 3.85 4.24
Spokane County 2.54 2.49 2.82 2.66 2.47 3.05 3.43 3.17 3.36 3.11 3.68 4.74
Locale 7
Great Northern School District
Cases, birth-19
Persons, birth-19
Note: The rates are the annual number of reported cases of gonorrhea, syphilis, or chlamydia in children (age birth-19) per
1,000 adolescents (age birth-19). Suppression code definitions for yearly rates are explained in Technical Notes. Due to
contractural agreement some data may not for populations less than 100.
State Source: Department of Health, Sexually Transmitted Disease (STD) Services, Sexually Transmitted Disease Reported
Cases. Population Estimates: Washington State Department of Health
Updated
3/15/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 33
Problem Outcomes: Child or Family Health
Suicide and Suicide Attempts (Age 10-17) Go To Standardized Five Year Rate Indicator Comparison Profile
140
Rate Per
120
100,000
100
80
60
40
20
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 63.43 56.03 45.61 57.23 51.86 50.99 42.79 56.73 52.01 48.75 38.72 48.11
Spokane County 129.44 95.41 87.51 95.44 78.89 66.77 64.78 74.94 98.65 88.37 54.86 90.42
Locale 7 19.52 19.51 78.25 117.53 38.08 95.29 38.80 77.22 38.30 112.61 36.98 127.18
Great Northern School District SP SP SP SP SP SP SP SP SP SP SP SP
Suicide & Attempt 0 0 0 0 0 0 0 0 0 0 0 0
Persons, 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rate is the annual number of adolescents (age 10-17) who committed suicide or were admitted to the hospital for
suicide attempts, per 100,000 adolescents (age 10-17). Suicides are based on death certificate information. Suicide attempts are
based on hospital admissions, but do not include admissions to federal hospitals. Suppression code definitions for yearly rates are
explained in Technical Notes. Due to contractural agreement data may not be displayed for locations with adolescent populations
less than 100.
State Source: Department of Health, Office of Hospital and Patient Data Systems, Comprehensive Hospital Abstract Reporting
System (CHARS) and Department of Health, Center for Health Statistics Death Certificate Data. Population Estimates:
Washington State Department of Health
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 34
Problem Outcomes: Child or Family Health
Low Birthweight Babies Go To Standardized Five Year Rate Indicator Comparison Profile
80
Rate Per 70
1,000 60
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 56.06 57.08 58.22 55.76 57.64 57.25 60.35 61.96 61.04 65.16 63.27 63.39
Spokane County 57.22 54.98 61.37 59.99 68.78 63.89 65.20 60.76 64.83 68.41 64.87 65.37
Locale 7 53.60 56.47 57.26 60.93 67.54 72.22 47.62 57.97 53.00 71.79 56.86 67.10
Great Northern School District SN SN SN SN SN SN SN SN SN SN SN SN
Low-weight Babies 0 0 0 1 0 0 0 1 0 1 1 0
All Births 5 5 4 5 6 6 5 5 5 7 6 7
Note: The rate is the annual number of babies born with low birthweight, per 1,000 live births. Low birthweight is less than
2,500 grams. Rate changes in data result from on-going updates to birth records. No rate is given when the number of live births
is less than 100 in the geographic area. Suppression code definitions for yearly rates are explained in Technical Notes.
State Source: Department of Health, Center for Health Statistics, Birth Certificate Data File
National Source: U.S. Department of Health and Human Services, Centers for Disease Control and Health Statistics National
Center for Health Statistics, Division of Health Services, WONDER Data System
Updated
12/14/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 35
Problem Outcomes: Child or Family Health
Injury or Accident Hospitalizations for Women Go To Standardized Five Year Rate Indicator Comparison Profile
30
Percent
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 10.61 10.75 10.55 11.08 11.73 11.93 12.25 13.21 13.32 13.53 13.45 14.27
Spokane County 13.08 13.44 12.39 12.25 13.66 13.27 15.80 17.03 17.37 17.46 17.25 19.78
Locale 7 10.17 11.05 9.37 11.09 10.58 11.10 14.29 15.24 15.21 15.45 15.72 19.03
Great Northern School District SN SN SN SN SN SN SN SN SN SN SN SN
Injuries 2 2 2 3 3 3 4 4 5 4 4 5
Hospitalizations 15 17 19 22 22 22 25 25 25 26 26 27
Note: The rate is the annual number of injury or accident hospitalizations for women as a percent of all hospitalizations for
women (age 18+). Suppression code definitions for yearly rates are explained in Technical Notes. Due to contractual agreement
data may not be displayed for areas with less than 100 hospitalizations.
State Source: Department of Health, Office of Hospital and Patient Data Systems, Comprehensive Hospital Abstract Reporting
System (CHARS) .
Updated
8/25/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 36
Problem Outcomes: School Issues
Weapons Incidents in School Go To Standardized Five Year Rate Indicator Comparison Profile
4
Rate Per 4
1,000 3
3
2
2
1
1
0
Great Northern School District State
Spokane County Locale 7
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
State 2.38 2.66 2.95 3.41 2.73 2.70 2.88 2.75 2.96 3.24 3.07 2.91
Spokane County 1.54 2.19 2.62 1.64 1.87 0.87 1.49 1.49 1.46 1.23 1.65 1.32
Locale 7 0.39 0.53 1.72 1.08 1.23 0.55 0.83 0.84 0.99 0.56 1.36 2.28
Great Northern School District 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Incidents 0 0 0 0 0 0 0 0 0 0 0 0
Enrollment 30 42 49 45 41 44 44 42 43 35 34 35
Note: The rate is the annual number of reported incidents of guns and other weapons at any grade level per 1000 students
enrolled in October for all grades.
State Source: Office of Superintendent of Public Instruction, Information Services, Safe and Drug-free Schools: Report to the
Legislature on Weapons in Schools RCW 28A.320.130
Updated
2/16/2010
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 37
Problem Outcomes: Criminal Justice
Offences, Domestic Violence Go To Standardized Five Year Rate Indicator Comparison Profile
25
20
Rate Per
15
1,000
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 7.80 7.63 6.86 6.92 6.77 6.51 6.51 6.46 6.47 6.06 5.79 5.32
Spokane County 9.50 9.93 8.38 8.23 8.61 7.87 8.59 7.44 7.18 6.43 6.88 6.66
Locale 7 UN UN UN UN UN UN UN 3.96 4.92 3.82 3.34 3.70
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Offences 4 4 3 3 3 3 4 2 2 2 2 2
Persons 533 557 572 582 597 598 569 581 624 715 780 849
Note: The rate is the annual number of domestic violence-related offences, per 1,000 persons. Domestic violence includes any
violence of one family member against another family member. Family can include spouses, former spouses, parents who have
children in common regardless of marital status, adults who live in the same household, as well as parents and their children.
Offences differ from arrests. While funding and grants are associated with participation, reporting is not mandatory. Offences are
incidence reporting. When more than one victim is involved an offence is filed for each victim. Multiple property violations
performed at the same incident are counted as one offence. However when both types of events happen, only the victim incidents
are reported as offences. Offences focus on the nature of the crime, while arrests focus on the apprehended accused perpetrator.
Many offences occur without arresting perpetrators.
Denominators are adjusted by subtracting the population of police agencies that did not report offences. In spite of this
population adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the rate for the county will
be lower than it would be if that jurisdiction was included. For percent subtracted and the agencies not reporting, see the
appendix on Non-Reporting Agencies and Population. Suppression code definitions for yearly rates are explained in Technical
Notes.
State Source: Washington Association of Sheriffs and Police Chiefs, UCR Division. Population Estimates: Washington State
Department of Health
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 38
Problem Outcomes: Criminal Justice
Total Arrests of Young Adolescents (Age 10-14) Go To Standardized Five Year Rate Indicator Comparison Profile
60
Rate Per
1,000 50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 47.77 42.14 37.85 36.84 31.69 27.82 27.87 26.57 23.29 22.20 21.42 19.99
Spokane County 47.97 50.42 43.40 44.93 41.39 21.15 24.78 17.10 17.77 14.64 14.13 25.59
Locale 7 UN UN UN UN UN UN UN 18.18 31.84 26.28 26.77 19.48
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-14 1 1 1 1 1 1 1 0 0 0 0 0
Adjst'd Pop 10-14 42 43 45 46 47 47 44 44 46 51 55 58
Note: The rate is the annual number of arrests of younger adolescents (age 10-14) for any crime, per 1,000 adolescents (age
10-14). Data may differ from our last report because of refinements to our population adjustment process. Denominators are
adjusted by subtracting the population of police agencies that did not report arrests to UCR. In spite of this population
adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the rate will be lower than it would be
if that jurisdiction was included. For percent subtracted, suppression code definitions and the agencies not reporting, see the
Technical Notes and the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 39
Problem Outcomes: Criminal Justice
Arrests (Age 10-14), Property Crime Go To Standardized Five Year Rate Indicator Comparison Profile
30
Rate Per
1,000 25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 23.92 21.45 18.07 16.32 13.05 11.96 11.84 10.97 9.47 8.64 8.60 7.48
Spokane County 25.75 27.39 21.04 19.33 18.08 12.71 13.18 7.74 6.23 4.97 5.11 10.83
Locale 7 UN UN UN UN UN UN UN 6.27 11.35 6.26 9.65 4.87
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-14 1 1 1 0 1 0 0 0 0 0 0 0
Adjst'd Pop 10-14 42 43 45 46 47 47 44 44 46 51 55 58
Note: The rate is the annual number of arrests of younger adolescents (age 10-14) for property crimes, per 1,000 adolescents
(age 10-14). Property crimes include all crimes involving burglary, larceny-theft, motor vehicle theft, and arson. Data may
differ from our last report because of refinements to our population adjustment process. Denominators are adjusted by
subtracting the population of police agencies that did not report arrests to UCR. In spite of this population adjustment, when the
non-reporting police jurisdiction is where much of the crime occurs, the rate for the area will be lower than it would be if that
jurisdiction was included. For percent subtracted, suppression code definitions and the agencies not reporting, see the Technical
Notes and the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 40
Problem Outcomes: Criminal Justice
Arrests (Age 10-17), Property Crime Go To Standardized Five Year Rate Indicator Comparison Profile
40
Rate Per 35
30
1,000
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 34.74 30.91 27.49 24.93 20.95 19.66 19.12 18.12 16.69 15.74 16.33 15.36
Spokane County 37.03 36.34 32.82 27.36 25.87 17.04 20.43 14.53 12.69 10.55 9.56 20.27
Locale 7 UN UN UN UN UN UN UN 11.68 15.06 10.41 14.73 11.08
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-17 2 2 1 1 1 1 1 0 0 0 0 0
Adjst'd Pop 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rate is the annual number of arrests of adolescents (age 10-17) for property crimes, per 1,000 adolescents (age 10-
17). Property crimes include all crimes involving burglary, larceny-theft, motor vehicle theft, and arson. Data may differ from
our last report because of refinements to our population adjustment process. Denominators are adjusted by subtracting the
population of police agencies that did not report arrests to UCR. In spite of this population adjustment, when the non-reporting
police jurisdiction is where much of the crime occurs, the rate for the county will be lower than it would be if that jurisdiction
was included. For percent subtracted, suppression code definitions and the agencies not reporting, see the Technical Notes and
the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 41
Problem Outcomes: Criminal Justice
Arrests (Age 18+), Property Crime Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per 9
1,000 8
7
6
5
4
3
2
1
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 7.90 7.27 6.82 6.52 6.30 6.21 6.50 6.82 6.73 6.10 6.13 5.61
Spokane County 7.78 8.30 8.27 7.40 7.58 4.04 5.15 4.55 4.55 3.38 3.29 3.85
Locale 7 UN UN UN UN UN UN UN 2.82 3.27 3.77 3.56 3.91
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 18+ 2 2 2 2 2 2 2 1 1 1 1 1
Adjst'd Pop 18+ 398 419 433 446 460 460 440 450 484 556 608 663
Note: The rate is the annual number of arrests of adults (age 18+) for property crimes, per 1,000 adults (age 18+). Property
crimes include all crimes involving burglary, larceny-theft, motor vehicle theft, and arson. Data may differ from our last report
because of refinements to our population adjustment process. Denominators are adjusted by subtracting the population of police
agencies that did not report arrests to UCR. In spite of this population adjustment, when the non-reporting police jurisdiction is
where much of the crime occurs, the rate for the county will be lower than it would be if that jurisdiction was included. For
percent subtracted, suppression code definitions and the agencies not reporting, see the Technical Notes and the appendix on
Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 42
Problem Outcomes: Criminal Justice
Arrests (Age 10-17), Violent Crime Go To Standardized Five Year Rate Indicator Comparison Profile
45
Rate Per 40
1,000 35
30
25
20
15
10
5
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 3.78 3.43 3.04 2.93 2.68 2.32 2.33 2.22 2.16 2.26 2.47 2.25
Spokane County 2.93 2.93 3.27 3.05 3.71 1.73 1.84 2.45 2.75 2.55 3.40 2.99
Locale 7 UN UN UN UN UN UN UN 2.14 2.51 2.84 2.61 2.73
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-17 0 0 0 0 0 0 0 0 0 0 0 0
Adjst'd Pop 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rates are the annual number of arrests of adolescents (age 10-17) for violent crime per 1,000 adolescents (age 10-
17). Violent crimes include all crimes involving criminal homicide, forcible rape, robbery, and aggravated assault. Simple assault
is not defined as a violent crime. Data may differ from our last report because of refinements to our population adjustment
process. Denominators are adjusted by subtracting the population of police agencies that did not report arrests to UCR. In spite
of this population adjustment, when the non-reporting police jurisdiction is where much of the crime occurs, the rate for the
county will be lower than it would be if that jurisdiction was included. For percent subtracted, suppression code definitions and
the agencies not reporting, see the Technical Notes and the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 43
Problem Outcomes: Substance Use
Alcohol-Related Traffic Fatalities Per All Traffic Fatalities
Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per 60
100
50
40
30
20
10
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 39.47 43.20 38.15 39.30 37.44 39.82 36.83 37.74 41.76 39.65 40.81 43.49
Spokane County 48.15 37.78 21.43 36.59 38.46 19.35 31.03 42.31 35.29 38.10 27.27 45.45
Locale 7
Great Northern School District
Alcohol-related
Fatalities
Note: The rates are the annual number of alcohol-related traffic fatalities, per 100 traffic fatalities. "Alcohol-related" means
that the officer on the scene determined that at least one driver involved in the accident "had been drinking." Thus, "Alcohol-
related" includes but is not limited to the legal definition of driving under the influence. Care should be taken since small
numbers of events can cause unreliable rates in some counties.
State Source: Washington State Patrol, Records Section, Traffic Collisions in Washington State, Accident Records Database
National Source: National Center for Statistics and Analysis, Fatal Accident Reporting System (FARS)
Updated
11/10/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 44
Problem Outcomes: Substance Use
Arrests (Age 10-17), Alcohol Violation Go To Standardized Five Year Rate Indicator Comparison Profile
14
Rate Per
12
1,000
10
8
6
4
2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 9.15 9.24 9.66 9.03 8.13 7.80 7.81 7.36 6.46 7.44 7.70 6.72
Spokane County 7.48 5.66 9.16 6.81 6.20 3.15 4.83 4.93 5.53 3.87 4.32 4.93
Locale 7 UN UN UN UN UN UN UN 11.68 9.85 8.89 10.07 6.90
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-17 0 0 0 0 0 0 0 0 0 0 0 0
Adjst'd Pop 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rates are the annual number of arrests of adolescents (age 10-17) for alcohol violations, per 1,000 adolescents (age
10-17). Alcohol violations include all crimes involving driving under the influence, liquor law violations, and drunkenness. For
children, arrests for liquor law violations are usually arrests for minor in possession.
1) Data may differ from our last report because of refinements to our population adjustment process. Denominators are adjusted
by subtracting the population of police agencies that did not report arrests to UCR. In spite of this population adjustment, when
the non-reporting police jurisdiction is where much of the crime occurs, the rate for the county will be lower than it would be if
that jurisdiction was included. For percent subtracted, suppression code definitions and the agencies not reporting, see the
Technical Notes and the appendix on Non-Reporting Agencies and Population.
2) The DUI portion of this measure is likely understated, because arrests made by the State Patrol (approximately 40% of DUI
arrests) are not attributable to counties. State Patrol arrests are included in the state rates.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 45
Problem Outcomes: Substance Use
Arrests (Age 10-17), Drug Law Violation Go To Standardized Five Year Rate Indicator Comparison Profile
10
Rate Per 9
1,000 8
7
6
5
4
3
2
1
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 5.39 4.83 4.89 5.16 5.19 4.86 4.87 4.22 4.31 4.52 4.62 4.31
Spokane County 4.14 5.20 4.30 5.36 5.78 2.38 4.52 4.73 4.59 4.89 4.25 5.03
Locale 7 UN UN UN UN UN UN UN 4.87 9.46 5.30 4.85 4.72
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Arrests, 10-17 0 0 0 0 0 0 0 0 0 0 0 0
Adjst'd Pop 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rates are the annual number of arrests of adolescents (age 10-17) for drug law violations, per 1,000 adolescents (age
10-17). Drug law violations include all crimes involving sale, manufacturing, and possession of drugs.
Data may differ from our last report because of refinements to our population adjustment process. Denominators are adjusted by
subtracting the population of police agencies that did not report arrests to UCR. In spite of this population adjustment, when the
non-reporting police jurisdiction is where much of the crime occurs, the rate for the county will be lower than it would be if that
jurisdiction was included. For percent subtracted, suppression code definitions and the agencies not reporting, see the Technical
Notes and the appendix on Non-Reporting Agencies and Population.
State Source: Washington Association of Sheriffs and Police Chiefs, Uniform Crime Report (UCR), Tables 40 and 50.
Population Estimates: Washington State Department of Health
National Source: US Department of Justice, Bureau of Justice Statistics Sourcebook of Criminal Justice Statistics Online
Updated
12/4/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 46
Problem Outcomes: Substance Use
Clients of State-Funded Alcohol or Drug Services (Age 10-17)
Go To Standardized Five Year Rate Indicator Comparison Profile
Rate Per
1,000 18
16
14
12
10
8
6
4
2
0
Great Northern School District State
Spokane County Locale 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
State 13.32 13.01 12.85 12.34 11.59 11.35 11.16 11.05 10.63 10.24 10.59 11.24
Spokane County 12.41 13.06 12.83 13.14 13.43 16.20 15.72 15.42 13.91 15.43 14.48 14.49
Locale 7 7.22 7.80 7.43 6.66 5.71 7.43 9.31 12.55 9.96 9.76 7.03 7.63
Great Northern School District UN UN UN UN UN UN UN UN UN UN UN UN
Admits, 10-17 1 1 1 1 1 1 1 1 1 0 1 0
Persons, 10-17 66 67 67 67 68 67 64 63 67 76 81 86
Note: The rates are the annual number of adolescents (age 10-17) receiving state-funded alcohol or drug services, per 1,000
adolescents 10-17. Counts of clients are unduplicated so that those receiving services more than once during the year are only
counted once for that year. State-funded services include treatment, assessment, and detox. Persons in Department of
Corrections treatment programs are not included. Updates have been done and result in some changes to 2000 data.
State Source: Department of Social and Health Services, Division of Behavioral Health and Recovery, Treatment and
Assessment Report Generation Tool (TARGET). Population Estimates: Washington State Department of Health
National Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode
Data Set (TEDS)
Updated
10/30/2009
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 47
Technical Notes
Topics:
Counting Alcohol- or Drug-related Deaths
Uniform Crime Report - Non-Reporting Police Jurisdictions
CORE-GIS Conversion Process and Weighted Reliability Index
Duplicated and Unduplicated Counts
Suppression Codes
Rates – Why is Raw Data Converted to Rates?
Counting Alcohol- or Drug-related Deaths
AOD deaths are identified by matching all the contributory causes of death from death certificate records to a list of
causes that are considered AOD-related. The deaths identified as AOD-related then may be summed to provide area
totals. Dividing the total AOD-related deaths by all deaths in an area gives the percent of all deaths that are alcohol and
drug related. Lists of underlying causes of death that are AOD-related have been developed in several studies. Citations
for these studies are listed prior to the AOD attribution tables. AOD-related deaths used in this report are determined
using a comprehensive assembly of disease, accident, and injury codes identified in those studies. The codes are based
upon the International Classification of Diseases, Ninth Revision (ICD-9) from 1990 to 1998 or International Classification
of Diseases, Tenth Revision (ICD-10) after 1998.
The identified AOD-related causes of death may be either fully attributable or sometimes attributable to alcohol or drugs.
Some contributory causes of death are explicit in their mention of alcohol or drugs. Examples include alcoholic cirrhosis
of the liver (ICD-9 code 571.2), alcohol and drug dependence syndromes (ICD-9 codes 303 and 304, respectively), and
drug poisonings (ICD-9 codes E850 through E859). All deaths of this sort are fully, or 100%, attributable to alcohol or
drug abuse and are considered direct AOD-related deaths.
Other contributory causes of death are related only sometimes to alcohol or drugs. For example, epidemiological studies
have shown that, among persons over 35 years of age, 60% of deaths due to chronic pancreatitis (ICD-9 code 577.1)
and 75% of malignant neoplasms of the esophagus (ICD-9 code 150) are alcohol-related. For persons of all ages, 42%
of motor vehicle traffic and nontraffic deaths (ICD-9 codes E810 through E825) are alcohol-related. The appropriate
percentage of such indirectly attributable deaths are also counted toward totals for AOD-related deaths.
The tables on the following pages characterize the different diseases, injuries, and accidents by: name, ICD-9 or ICD-10
code, percent attributable to alcohol or drugs, age of inclusion. Information sources are listed below.
1. Schultz J, Rice D, & Parker D. 1990. Alcohol-related mortality and years of potential life lost - United States, 1987.
Morbidity and Mortality Weekly Report, 39, 173-178.
2. Rice D, et al. 1990. The Economic Costs of Alcohol and Drug Abuse and Mental Illness: 1985. Report submitted to
the Office of Financing and Coverage Policy of the Alcohol, Drug Abuse, and mental health Administration, U.S.
Department of Health and Human Services. San Francisco, CA: Institute for Health and Aging, University of California.
3. Fox K, Merrill J, Chang H, & Califano J. 1995. Estimating the Costs of Substance Abuse to the Medicaid Hospital Care
Program. American Journal of Public Health, 85(1), 48-54.
4. Seattle-King County HIV/AIDS Epidemiology Unit and Washington State Office of HIV/AIDS Epidemiology and
Evaluation. 1994. Washington State/Seattle-King County HIV/AIDS Epidemiology Report (2nd Quarter, 1994), p. 4.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 48
Technical Notes
Disease Category ICD-10 Code ICD-9 Code Attrib Age
Diseases Directly Attributable to Alcohol
Alcoholic psychoses F10, F10.3-F10.9 291 100% >=15
Alcohol dependence syndrome F10.2 303 100% >=15
Alcoholic polyneuropathy G62.1 357.5 100% >=15
Alcoholic cardiomyopathy I42.6 425.5 100% >=15
Alcoholic gastritis K29.2 535.3 100% >=15
Alcoholic fatty liver K70.0 571.0 100% >=15
Acute alcoholic hepatitis K70.1, K70.4 571.1 100% >=15
Alcoholic cirrhosis of the liver K70.3 571.2 100% >=15
Alcoholic liver damage, other K70.2, K70.9, K70 571.3 100% >=15
Excessive blood level of alcohol, R78.0, T51 790.3. 980 100% >=0
toxic effect of alcohol
Accidental poisoning by alcohol X45, Y15 E860 100% >=0
Nondependent abuse of Alcohol F10.1 305.0 100% >=0
E24.4
Alcohol-induced pseudo-Cushing's syndrome Not Available in ICD-9 100% >=15
Degeneration of nervous system due to alcohol
G31.2 Not Available in ICD-9 100% >=15
Alcoholic myopathy G72.1 Not Available in ICD-9 100% >=15
Maternal care for (suspected) damage to fetus from alcohol
O35.4 Not Available in ICD-9 100% >=15
Newborn affected by maternal use of alcohol
P04.3 Not Available in ICD-9 100% >=0
Fetal alcohol syndrome (dysmorphic)
Q86.0 Not Available in ICD-9 100% >=0
Suicide attributable to alcohol X65 Not Available in ICD-9 100% >=0
Alcoholic Pellagra E52 265.2 100% >=0
Diseases Indirectly Attributable to Alcohol
Neoplasms
Breast C50, D05 174.0-174.9, 233.0 13% F >=35
Esophagus C15, D00.1 150.1-150.9, 230.1 75% >=35
Larynx C32 , D02.0 161.0-.161.9, 231.0 50% >=35
M,
40% F
Lip, oral cavity, pharynx C00-C14, D00.0 140.1-141.9, 143.0-149.9, 230.0 50% >=35
M,
40% F
Liver C22, D01.5 155.0-155.2, 230.8 29% >=35
Cardiovascular
Cardiomyopathy I42.0 - I42.2, I42.5, I42.7- I42.9 425.1, 425.4, 425.9 40%M >=35
Hypertension I10-113, O10-O14, O16 401.0-404.9, 642.0, 642.2, 642.9 11% >=35
Digestive System
Cirrhosis K71.7, K74.5-K74.6 571.5 74% >=35
Duodenal Ulcers K26 532.0-532.9 10% >=35
Pancreatitis, acute K85 577.0 47% >=35
Pancreatitis, chronic K86.1- K86.3, K86.9 577.1, 577.2, 577.9 72% >=35
Other Diseases or Conditions
Epilepsy G40.3,G40.4,G40.6,G40.9 345.1, 345.3, 345.9 30% >=15
Seizures R56 780.3 41% >=15
Tuberculosis A16-A19 011-013, 017, 018 25% >=15
Accident or Injury Causes: Motor V02–V04, V09.0, V09.2, V12–V14, E810-E825 42% >=0
vehicle traffic and non-traffic V19.0–V19.2, V19.4–V19.6, V20–V79,
accidents V80.3– V80.5, V81.0–V81.1, V82.0–V82.1,
V83–V86, V87.0–V87.8, V88.0–V88.8,
V89.0, V89.2
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 49
Technical Notes
Disease Category ICD-10 Code ICD-9 Code Attrib Age
Pedal cycle and other road vehicle V01, V05–V06, V09.1, V09.3–V09.9, E826-E829 20% >=0
accidents V10–V11, V15–V18, V19.3, V19.8–V19.9,
V80.0–V80.2, V80.6–V80.9, V82.2–V82.9,
V87.9, V88.9, V89.1, V89.3, V89.9
Water transport accidents V90-V94 E830-E838 20% >=0
Air & space transport accidents V95-V97 E840-E845 16% >=0
Accidental falls W00-W19 E880-E888 35% >=15
Accidents caused by fire X00-X09 E890-E899 45% >=0
Accidental drowning and W65-W74 E910 38% >=0
submersion
Suicides due to alcohol or drugs are now considered direct AOD-related deaths, other suicides are not apportioned. This brings our
Homicide &into compliance with NCHS definitions.
definitions other purposely X86–Y09, Y87.1 E960-E962, E962.1-E969 46% >=15
inflicted injury
Other X31, W79, W50-W52, W20- W34, Y15-Y19 E901, E911, E917-E920, E922 25% >=15
Other category includes: Excessive cold, Choking on food in airway; Striking against or struck accidentally by objects or persons;
Diseases Directly in or between objects;
Caught accidentally Attributable to DrugsAccidents caused by machinery; Accidents caused by cutting and piercing instruments.
Drug psychoses F11-F16, F18-F19 292 100% >=0
Drug dependence syndrome F11-F16, F18-F19 304 100% >=0
Polyneuropathy due to drugs G62.0 357.6 100% >=15
Drug dependence during F11-F16, F18-F19 648.3 100% >=0
pregnancy
Suspected damage to fetus from O35.5, 655.5 100% >=0
drugs
Noxious influences affecting fetus P04.4 760.7 100% >=0
Drug reactions, intox., withdrawal P96.1 779.4, 779.5 100% >=0
specific to newborn
Selected drug poisonings R78,R78.1-R78.6, T38 ; excludes Y40-59.9 962, 965, 967-971, 977 excludes 100% >=0
(therapeutic use) E930-949
Selected accidental drug X40-X44 E850-E858 100% >=0
poisonings
Accidental Poisonings (magic X46-X49 E861-E869 100% >=0
mushrooms, huffing and other
drug use)
Nondependent abuse of drugs F11-F16, F18-F19 305.2-305.9 100% >=0
Assault by poisoning using drugs x85 E962.0 100% >=0
and medicaments
Drug induced myopathy G72.0 Not Available in ICD-9 100%
Poisoning by drugs, accidentally or Y10-Y14 E980.0-E980.5 100% >=0
purposely inflicted
Suicides attributable to drugs x60-64 E950.0-E950.5 100% >=0
Diseases Indirectly Attributable to Drugs
AIDS (from IV drug use exposure) B20-B24 042.0-044.9 5% >=15
Cardiovascular
Endocarditis I33.0, I33.9 421.0, 421.9 75% >=15
Other
Hepatitis A B15.9 70.1 12% >=15
Hepatitis B B16-B16.9 70.2, 70.3 36% >=15
Hepatitis C B17-B19.9 70.5, 70.9 10% >=15
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 50
Technical Notes
Uniform Crime Report - Non-Reporting Police Jurisdictions
Most law enforcement agencies report arrest and offence data to the Washington Association of Sheriffs and Police Chiefs
(WASPC), which in turn provides data to the FBI‟s Uniform Crime Reporting Program. This is the source of our data.
Some jurisdictions do not report all arrests and offences, some report partial years, and some withhold certain categories
of arrests or offences. Reporting is voluntary for arrests and offences. Offences are more likely to be reported since some
funding is associated with reporting. Offences are incidence reporting. When more than one victim is involved an
offence is filed for each victim. Multiple property violations performed at the same incident are counted as one offence.
However when both types of events happen, only the victim incidents are reported as offences. Offences focus on the
nature of the crime, while arrests focus on the apprehended accused perpetrator. Many offences occur without arresting
perpetrators. Sometimes charges are dropped and sometimes no perpetrator is ever found. No perpetrator age can be
assigned to offence data so the entire age range of population is used as the denominator. Some data is reported to
UCR in a new system which is not yet compatible with UCR output reports and UCR cannot extract that data for this
report but does include it in their reports to the FBI. We list those jurisdictions as non-reporting although UCR considers
them to have reported. Only part one offences are reported in the Uniform Crime Report, some agencies have no part
one crimes to report. Those agencies are listed with zero events, not as non-reporting.
Information on the Non-reporting Population and Non-reporting Agencies are available only in the individual county and
locale level reports. Each area report shows how and when that area's police jurisdictions reported data to the
Washington Association of Sheriff's and Police Chiefs. If your area is one with jurisdictions having a significant amount of
incomplete data, be very careful that you adjust your risk assessment to reflect this. In other words, the reported arrest
rates may not adequately reflect the entire area. This will be true especially in those cases where the non-reporting
police jurisdictions have either very high or very low arrest rates, compared to the rest of the area.
In order to compensate for missing police reports, we have adjusted the denominator in the rate calculation so that it
reflects only the proportion of the area for which we do have data. For instance, say area A, with a population of 40,000,
has eight police districts. Now, if one of the police districts in the area did not report their arrests, the number of arrests
would not be representative of the whole area. Therefore, we would not want to use the population of the whole area in
the denominator because that would make the rate lower than it should be. The solution used in this report is to
subtract the population of that missing police district from the area population. We follow the same procedure for police
districts that report partial years: if they report only six months, we use only half of the population to calculate the rate.
In 2004 we have made adjustments to the process which calculates non-reporting at the County Like Us and State
levels. This has resulted in greater accuracy, but different rates than were previously reported in some counties and for
some years.
Due to the uneven geographic distribution of crime, missing police data can cause spikes or dips in the trend data
comparison of multiple consecutive years. We do not run into this problem in the state report because the county rates
there (as opposed to the individual county reports) only report 5-year averages. However for individual county reports
and reports for smaller areas like locales or districts the trend data can become unstable due to non-reporting.
Alternately, the conversion of data from certain police jurisdictions to other areas like locales may not apportion directly
causing too much of the data to be apportioned based on population rather than clearly assigned to one area. We use a
weighted reliability index (WRI) to determine when the conversion is no longer reliable. An explanation of that process
follows. We have tried to compensate for these and other issues by suppressing data which is likely to be affected.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 51
Technical Notes
CORE-GIS Conversion Process and Weighted Reliability Index
CORE-GIS obtains data from more than fifty government agency sources. The data are represented as events (e.g. # of
teen births, # of crimes, # of clients) occurring within a given geographic unit. This geographic unit is generally the
smallest that can be obtained from the agency source. For example, data may be available by school district, by zip
code, by census tract or by police jurisdictions. CORE-GIS calls these geographic units the “source geography.”
CORE-GIS data is usually reported at the geographic level of county or community – called in the rest of this report the
"destination geography." Therefore, data usually needs to be converted from the “source geographies” to the
“destination geography.”
The conversion is based on an overlay process, in which the events occurring in small source geographies that are totally
contained within the destination are combined with synthetic estimates of events occurring in source geographies that
are partly within and partly outside the destination geography.
The synthetic estimation is weighted by the population distribution between the source and destination areas. Therefore,
it requires a small-scale count of the population underlying both source and destination geographies. This process is
explained below through examples.
Data being converted from a smaller geography (source geography) like school district to a larger geography (like a
county) is usually fairly reliable because most of the smaller pieces fit neatly and wholly into the new geography. (See
example 1).
The rectangles represent two possible data source geographies (one densely populated school district – Urban School
District -- and one thinly populated school district – Suburban School District -- surrounding it). The large oval
represents a report's destination geography such as county, locale or network.
Example 1 Suburban School District (thinly populated)
Urban School District
(densely populated)
The following statements refer to the first example:
All of the events occurring in the urban school district can be attributed entirely to the destination geography.
The events occurring in the split source geography (suburban school district, in this example) are distributed to the
destination geography in the same proportion as the underlying population is distributed. If 40% of the suburban
school district population lies within the destination geography, then 40% of its events are attributed to the destination
geography.
These events are split by age, race and gender subgroups whenever possible, as are the populations. So the synthetic
estimation is broken down that way also. If 40% of the young White population of the suburban school district lives in
the destination geography, then 40% of the events occurring to young White people are attributed there. If, on the
other hand, only 10% of the young American Indian population of the suburban school district lives in the destination
geography, then only 10% of the events occurring to young American Indian people are attributed there.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 52
Technical Notes
While we can develop an algorithm to distribute all source geography populations to all destination geography
populations, that distribution will not always be reliable.
For example, see the situation depicted in Example 2 below. Here we are trying to estimate the number of events
contained in two very small destination geographies (the ovals). Could this synthetic estimate be reliable? Perhaps, if
the small area within the ovals really is representative of the whole area -- but more likely not.
Example 2
A statistic is needed to assist researchers in determining when a destination geography's events cannot be reliably
estimated using these processes. For CORE-GIS, that statistic is the Weighted Reliability Index (WRI).
The amount of overlap between source and destination populations can vary from less than 1% to 99% -- only a little of
a source population can live in a destination, or almost all of the source population can live in a destination.
The key underlying assumption behind the CORE-GIS Weighted Reliability Index is as follows:
When most of the population for the source geography is also in the destination geography, we
can be more certain of the reliability of the estimation process.
Therefore, the weighting process lets us calculate, for each source-geography/destination-geography combination, the
reliability of each destination geography's estimate.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 53
Technical Notes
In the figure for Example 3, for zip code 2 the source area population is mostly in the destination oval (encased in the
dashed line), but the majority population from the other contributing source area is not.
Example 3
Zip code 2
100
Zip code 1
900
10
70
The oval represents the destination geography boundary -- the edge of a destination city. The rectangles represent the
source geography boundaries for two zip codes. The numbers are population of people living in each place: 10 people
live both in Destination City and in the first source (Zip code 1), and 900 people live both in Destination City and in the
second source (Zipcode2).
The formula for Weighted Reliability Index for a single destination is the total weighted destination population as a
percent of total population. To understand this formula, see the calculations below.
Percent of source population Multiplied by the population Amount of
attributed to destination attributed to the destination destination
population
zip code 1 10/80 = 12.5% * 10 1.25
zip code 2 900/1000 = 90% * 900 810.00
Total for Destination 910 811.25
In the above example, the Weighted Reliability Index for Destination City is 811.25 / 910 = 89%. Basically, 89%
of the event locations were directly attributed to the area they occurred. Along with the WRI a cut point for
reliable reporting is needed. When half or more of the events have been imputed to the destination geography, rather
than directly attributed from the source geography, the data is considered unreliable and rates are suppressed.
WRI for Areas with Non-Reporting of Data
There is a second way that data may become unreliable. Some police jurisdictions do not report data to the state
sources, use a reporting method which cannot be included in our files, fail to report for either adults or juveniles, or
report for only part of a year. This is particularly true for court data – arrests or offenses. In order to accurately
evaluate the reliability of data conversions for destination geographies containing those jurisdictions, non-reporting
jurisdiction populations were excluded from the calculations for WRI and the non-reporting jurisdiction issue is evaluated
separately.
Partial Reporting, part of a year or part of a population, is also taken into consideration when computing the percentage
of non-reporting in a destination geography. Adult and juvenile rates are evaluated separately. Some areas may pass for
one, but not for the other due to their reporting habits. For partial year reporting the percentage of the year with data
reported is used to evaluate each category.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 54
Technical Notes
Example 4
3
Non-reporting Jurisdiction
50 5
3 reporting
jurisdiction 2
4
30
3
The second test of reliability is to determine whether the population for the rate is adequately represented. In this
example, allow the numbers inside the oval to represent a population of 100 allocated to the destination geography. Two
source jurisdictions are entirely located in the destination geography represented by the oval. Their events when
reported would be directly attributed. The non-reporting jurisdiction would have its population of 50 excluded from the
calculation for WRI, while the reporting jurisdiction would have its population included in the calculation. In this case the
completely contained reporting jurisdiction would represent 30 of the remaining 50 population (60%) in the destination
oval. The imputed portion is 40% allowing the destination geography to pass the first test for WRI.
CORE-GIS also requires that the excluded non-reporting jurisdiction population (50 of 100) are less than 50% of the
total population for the destination geography. With an exclusion rate of 50%, this destination geography would fail the
reliability criteria.
The reliability of arrest rates is calculated each year based on non-reporting. For five year rates, three out of five data
years must be considered reliable by both tests and the average of the yearly WRI for all five years must reach the WRI
cut point value.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 55
Technical Notes
Duplicated and Unduplicated Counts
In an unduplicated person count, each person is counted only once in a year for the specified activity or service type,
even if they receive that service multiple times during the year. Examples include Temporary Assistance to Needy
Families (TANF) Child Recipients, Food Stamp Recipients, and alcohol or drug treatment. Duplicated counts are made of
events such as prison admissions, arrests, births, or admission to a hospital for attempted suicide. For instance, each
time a person is admitted to a prison, that “event” is counted. Therefore, a person admitted more than once is included
more than once in the total count.
Suppression Codes for Yearly Trend Data
UN=Unreliable conversion of events to report geography, failure of weighted reliability index (WRI). The WRI
evaluation process is further explained in the section labeled „CORE-GIS Conversion Process and Weighted Reliability
Index‟.
SP=Suppressed by agreement with data provider when denominator is below agreed level and may compromise a
person's rights to confidentiality.
SN=Small Number Sample. Geography has less than 30 events in the denominator. More reliable at 5 year level or for
larger area.
NR=Not reliable due to non-reporting of police jurisdictions data. Fifty percent or more of the population is not
represented by the data due to non-reporting jurisdictions.
Rates: why is “raw data” converted to rates?
In order to make comparisons between counties and the state, and between counties that have different sizes, we use
rates to describe an event in terms of a standard size population---either per 100 (percent), per 1,000 or per 100,000.
For instance, what does it mean if County A has 42 alcohol retail licenses, and County B has 399? Does it mean that
based on this indicator, the risk factor (Availability) is much higher in County B than it is County A? No, not if County B
is a much bigger county. If County B is bigger, then the “rate” of liquor licenses per population might be the same or
even lower. The only way to compare them is to convert the raw numbers to rates, based on the same population
factor.
For instance:
County A: # of licenses – 42, # of persons (all ages) – 14, 297
County B: # of licenses – 399, # of persons (all ages) – 186,185
To calculate the rate per 1,000:
42 / 14,297 = .002937 .002937 X 1,000 = 2.94
399 / 186,185 = .002143 .002143 X 1,000 = 2.14
So the rate of alcohol retail licenses is 2.94 per 1,000 people in County A, and 2.14 per 1,000 people in County B.
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 56
Population of Areas Not Reporting Arrests or Offences
Great Northern School District #
Populations subtracted for police agencies not reporting
Police agencies are not required to report arrests or offences to UCR, they do so voluntarily. For a variety of reasons, a
jurisdiction may report part or none of the arrests or offences for a year. In these cases, the denominator is the population
of the areas that did report. For example, if juvenile arrests for one agency are not reported, the juveniles for that
jurisdiction are not included in the population denominator either.
The tables below show the values that comprise the adjustment for your county for each age range we report. "%
Subtracted" is the percent of the county's population subtracted for non-reporting. "Subtracted" is the amount subtracted.
"Persons" is the locale's population. "Adjst'd Pop" is the denominator used to calculate indicator rates.
Nevertheless, rates can differ markedly from year to year particularly if a jurisdiction, where most of the crime in the
county occurs, did not report. When 50% or more of the population is not reported the yearly rate is suppressed.
Jurisdictions crossing county boundary lines are apportioned to each area by age, and sex of the population. When more
than 40% of the reported events have been apportioned, "synthetically estimated", the yearly rate is suppressed.
All Arrests for 10-14 year olds have 5 year rates which represent 100.00 % of the population.
Adjustments for non-reporting Arrests (age 10-14)
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
% Subtracted 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Subtracted, 10-14 0 0 0 0 0 0 0 0 0 0 0
Persons, 10-14 43 45 46 47 47 44 44 46 51 55 58
Adjst'd Pop 10-14 43 45 46 47 47 44 44 46 51 55 58
All Arrests for 10-17 year olds have 5 year rates which represent 100.00 % of the population.
Adjustments for non-reporting Arrests (age 10-17)
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
% Subtracted 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Subtracted, 10-17 0 0 0 0 0 0 0 0 0 0 0
Persons, 10-17 67 67 67 68 67 64 63 67 76 81 86
Adjst'd Pop 10-17 67 67 67 68 67 64 63 67 76 81 86
All Arrests for adults have 5 year rates which represent 100.00 % of the population.
Adjustments for non-reporting Arrests (age 18+)
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
% Subtracted 0.00 0.00 0.00 0.00 0.86 0.90 0.00 0.00 0.00 0.00 0.00
Subtracted, 18+ 0 0 0 0 4 4 0 0 0 0 0
Persons, 18+ 419 433 446 460 464 444 450 484 556 608 663
Adjst'd Pop 18+ 419 433 446 460 460 440 450 484 556 608 663
All Offences for persons have 5 year rates which represent 100.00 % of the population.
Adjustments for non-reporting Offences
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
% Subtracted 0.00 0.35 0.85 0.83 1.00 1.04 0.00 0.00 0.00 0.00 0.00
Subtracted, 18+ 0 2 5 5 6 6 0 0 0 0 0
Persons, 18+ 557 573 587 602 603 575 581 624 715 780 849
Adjst'd Pop 18+ 597 597 569 581 624 715 780 849
Washington State Department of Social and Health Services, Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS) 57
Agencies Not Reporting Arrests and/or Offences
Great Northern School District Back to Population Deducted
Percent of Adult Arrests Not Reported to UCR by Year
Police agency jurisdictions which are located at least partially in your district are listed below. The table shows the
percentage of non-reporting by jurisdiction for each year.
Jurisdictions 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Airway Heights PD 100.0 100.0
Spokane CO
Spokane PD 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 58
Agencies Not Reporting Arrests and/or Offences
Great Northern School District Back to Population Deducted
Percent of Juvenile (Age 10-17) Arrests Not Reported to UCR by Year
Police agency jurisdictions which are located at least partially in your district are listed below. The table shows the
percentage of non-reporting for juvenile arrests each year.
Jurisdictions 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Airway Heights PD 100.0 100.0
Spokane CO
Spokane PD 100.0 100.0 100.0 100.0 100.0 100.0
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 59
Agencies Not Reporting Arrests and/or Offences
Great Northern School District Back to Population Deducted
Percent of Offences Not Reported to UCR by Year
Police agency jurisdictions which are located at least partially in your district are listed below. The table shows the
percentage of non-reporting for offences each year.
Jurisdictions 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Airway Heights PD 33.0 92.0 92.0 100.0 100.0
Spokane CO
Spokane PD
Washington State Department of Social and Health Services
Research and Data Analysis,
Community Outcome and Risk Evaluation Geographic Information System (CORE-GIS). Community Reports, December 2009. 60
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